Are Forecasts Supposed to be Accurate?

According to various the media, the government’s new analysis of the impact of Brexit says the UK would be worse off outside the European Union under every scenario modelled (Source: Buzfeed News) This analysis claimed that compared to the current forecasts UK growth would be 5% lower over the next 15 years under a comprehensive free trade agreement with the EU. But the government has written this analysis down as obsolete as the previous forecast accuracy hasn’t been perfect and therefore claimed to be another form of oppositions scaremongering. But there is an inherited problem with that statement. Forecast accuracy can never be 100 percent, in fact, it is highly unlikely that even a Nostradamus would get them right.

Unsuitable software

The unsuoitable software is a common denominator a forecast accuracy. This is especially common when using excel worksheets, that often have a number of mistakes and can be difficult to collaborate on. A common theme among worksheet users is that a single number can skew the data and impact forecast’s accuracy, and thus produce an inaccurate picture. It is also possible that an enterprise using a software assign untrained or inexperienced forecasters. To solve this companies’ use specialty software and have experienced data analysts and financial professionals working with their forecasts. However, this doesn’t have to be the case all of the time, software, like ProForecast, offers forecasting software that gives you a variety of choices when it comes to your business models, and is easy to use. On top of that, we use AI to help your forecasts and alert you every time there is a discrepancy in your data.

There’s no time machine

Another problem that forecasts face is future predictions. A number of future scenarios are created, and often they are based on PESTL judgments and SWOTs of the business. But that is where the majority of the problems arise. When forecasting, just a sales projection isn’t enough, thus a business must adjust and model to the potential future scenarios in their market, and this is where it gets tricky. Predicting the future, like in this case, was predicting post-Brexit Britain isn’t fully plausible if you don’t have a time machine. Therefore, all of the scenario forecasts will include slight discrepancies to actual reality. Additionally, a lot of the future prediction will depend on the actual market volatility, demand for the product, popular trends, and a forecasters’ bias. But this doesn’t mean that your forecast should be written off because you can never create something that doesn’t have your bias attached to it. This only means that a true forecaster will point this out, and account for potential errors, and make everyone aware of the biases, while the organisation receiving the forecast should acknowledge the discrepancies and prepare to adapt.

Forecasts aren’t only about the accuracy!

We have discussed this issue previously as well as how to improve your forecasting accuracy in the article on demand volatility, but there is an important issue that everybody tends to forget, is that forecasts aren’t only about accuracy and measuring the future of the economy and its impacts (again-impossible!!!). Forecasts are crucial for planning and business strategy, it’s OK if they don’t match with military precision with the market demand. At the end of the day, the execution from delivery teams cannot be predicted, the market will fluctuate on its own terms and can depend on things like weather, which we all know… So, as long as your data produced an acceptable plan that had timely execution and enough leverage for the time being to make the organisation sustainable – success! In the meantime, continuous forecasting and repeated measuring to the reality will make forecasts more accurate and more precise.

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